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Simple correlation for estimating the global solar radiation on horizontal surfaces in India

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  • Katiyar, A.K.
  • Pandey, Chanchal Kumar

Abstract

A long range five years (2001–2005) measured data of the global solar radiation on horizontal surface along with the bright sunshine hours of four prominent cities viz. Jodhpur, Calcutta, Bombay, and Pune of India have been analyzed. The under considered cities have varying weather conditions of the country. The regression constants have been calculated for the first, second and the third order Angstrom type correlations for each location using regression analysis method. Comparisons of monthly mean global solar radiation (H¯) between the measured and the calculated values have been made. The statistical errors are also performed for testing the accuracy of regression constants. It is observed that in comparison to first order, second and the third order Angstrom type correlations do not improve the accuracy of the estimated global radiation. Therefore, using the measured data of all four cities together, we developed the first order Angstrom type correlations and presented new regression constants, applicable to all Indian locations. Furthermore, these regression constants of all India correlation are validated by comparison with the experimental and the other theoretical results available in literature.

Suggested Citation

  • Katiyar, A.K. & Pandey, Chanchal Kumar, 2010. "Simple correlation for estimating the global solar radiation on horizontal surfaces in India," Energy, Elsevier, vol. 35(12), pages 5043-5048.
  • Handle: RePEc:eee:energy:v:35:y:2010:i:12:p:5043-5048
    DOI: 10.1016/j.energy.2010.08.014
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    7. Bayrakçı, Hilmi Cenk & Demircan, Cihan & Keçebaş, Ali, 2018. "The development of empirical models for estimating global solar radiation on horizontal surface: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2771-2782.
    8. Chen, Ji-Long & He, Lei & Yang, Hong & Ma, Maohua & Chen, Qiao & Wu, Sheng-Jun & Xiao, Zuo-lin, 2019. "Empirical models for estimating monthly global solar radiation: A most comprehensive review and comparative case study in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 91-111.
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    11. Paulescu, M. & Stefu, N. & Calinoiu, D. & Paulescu, E. & Pop, N. & Boata, R. & Mares, O., 2016. "Ångström–Prescott equation: Physical basis, empirical models and sensitivity analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 495-506.
    12. Ener Rusen, Selmin & Hammer, Annette & Akinoglu, Bulent G., 2013. "Estimation of daily global solar irradiation by coupling ground measurements of bright sunshine hours to satellite imagery," Energy, Elsevier, vol. 58(C), pages 417-425.
    13. Despotovic, Milan & Nedic, Vladimir & Despotovic, Danijela & Cvetanovic, Slobodan, 2015. "Review and statistical analysis of different global solar radiation sunshine models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1869-1880.
    14. Jamil, Basharat & Akhtar, Naiem, 2017. "Comparative analysis of diffuse solar radiation models based on sky-clearness index and sunshine period for humid-subtropical climatic region of India: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 329-355.
    15. Khalil, Samy A. & Shaffie, A.M., 2016. "Evaluation of transposition models of solar irradiance over Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 105-119.
    16. Halawa, Edward & GhaffarianHoseini, AmirHosein & Hin Wa Li, Danny, 2014. "Empirical correlations as a means for estimating monthly average daily global radiation: A critical overview," Renewable Energy, Elsevier, vol. 72(C), pages 149-153.
    17. Makade, Rahul G. & Jamil, Basharat, 2018. "Statistical analysis of sunshine based global solar radiation (GSR) models for tropical wet and dry climatic Region in Nagpur, India: A case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 87(C), pages 22-43.
    18. Escrig, H. & Batlles, F.J. & Alonso, J. & Baena, F.M. & Bosch, J.L. & Salbidegoitia, I.B. & Burgaleta, J.I., 2013. "Cloud detection, classification and motion estimation using geostationary satellite imagery for cloud cover forecast," Energy, Elsevier, vol. 55(C), pages 853-859.

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